1. Technical Field
The present invention relates to a method, an apparatus, and a computer program product for calculating current distribution inside a brain, and in particular to a method, an apparatus, and a computer program product for calculating current distribution inside a brain, by which a solution can be obtained in a short time with a high resolution in-brain current distribution.
2. Description of the Related Art
In recent years, BMI (Brain Machine Interface) has been researched. BMI is a technology for controlling motion of a robot or operation of other devices not by manual control, but by mere thinking about the motion/operation; to operate the robot and other devices, human brain waves (scalp potentials) or brain's magnetic fields (i.e., magnetic fields around a head) are detected in BMI. In BMI, while human brain activity is presumed based on human brain waves or magnetic fields per se, attempts have been made to presume in detail in which part in the human brain (not only on the surface of the head but also at a three-dimensional region within the brain) currents flow, based on this electromagnetic information, to more precisely presume activity within the human brain. A technology for estimating currents inside a human brain based on brain waves is referred to as an EEG (electroencephalography) inverse problem, while a technology for estimating currents inside a human brain based on magnetic fields produced by currents occurring in the brain is referred to as an MEG (magnetoencephalography) inverse problem.
In the EEG inverse problem and the MEG inverse problem, a lead field matrix for deriving an electric potential or a magnetic field from current source distribution (in-brain currents) can be obtained, and the current source can be estimated from this lead field matrix. See, for example, Japanese Laid-open Patent Application Publication No. 2003-38455.
To solve the EEG inverse problem and the MEG inverse problem, the head of a human body can be approximated to a sphere so that currents inside the brain can be calculated at high speeds. See Sarvas, “Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem,” Phys. Med. Biol., vol. 32, pp. 11-22, 1987. See also D. Yao, “Potential Produced by a Dipole in a Homogeneous Conducting Sphere,” IEEE Trans. Biomed. Eng. vol. 47, pp. 964-966, 2000. However, this method has a problem with precision because the actual shape of the head is not reflected in the calculation. Further, in the case of the MEG inverse problem, there is a property that if a current source faces in the radial direction in a homogenous sphere model, an external magnetic field of the current source becomes zero. This greatly restricts the possibility that in-brain currents can be analyzed.
For this reason, attempts have been made to calculate a current source using various numerical analytical methods which take into account the actual shape of a human head. See A. Crouzeix, “Méthodes de localisation des générateurs de l'activité électrique cérébrale à partir de signaux électro- et magnéto-encépahlographiques”, Rapport de thèse, Institution National des Sciences Appliquées de Lyon, pp. 11-31, 2001. In this method, the human head is represented using a mesh model, and current sources are obtained by BEM (Boundary Element Method) or by FEM (Finite Element Method). All references discussed herein, including patent and non-patent literature, are incorporated by reference into the present application. Using these numerical analytical methods, the shape of the human head can be faithfully reflected without restrictions as caused by the sphere approximation, so that in-brain currents can be calculated with high degree of accuracy.
However, these numerical analytical methods require a high degree of computational complexity and thus take considerable computation time. In a numerical analytical method, the complexity is largely dependent on the number of grid points constituting a grid. If a grid with a large pitch is used, the complexity will be reduced accordingly. However, this will cause a decrease in the calculation precision. As a result, a highly precise (high resolution) solution cannot be obtained if the complexity is reduced so much.
In view of the above, it would be desirable to provide a method, an apparatus, and a computer program product for calculating currents inside a brain, by which a solution can be obtained in a short time with a high resolution in-brain current distribution.